| A comprehensive profile of circulating RNAs in human serum SU Umu, H Langseth, C Bucher-Johannessen, B Fromm, A Keller, ... RNA biology 15 (2), 242-250, 2018 | 55 | 2018 |
| Robust identification of noncoding RNA from transcriptomes requires phylogenetically-informed sampling S Lindgreen, SU Umu, ASW Lai, H Eldai, W Liu, S McGimpsey, ... PLoS Comput Biol 10 (10), e1003907, 2014 | 37 | 2014 |
| A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life SU Umu, PP Gardner Bioinformatics 33 (7), 988-996, 2017 | 28 | 2017 |
| Avoidance of stochastic RNA interactions can be harnessed to control protein expression levels in bacteria and archaea SU Umu, AM Poole, RCJ Dobson, PP Gardner eLife 5, 2016 | 23 | 2016 |
| A probabilistic approach to microRNA-target binding H Oğul, SU Umu, YY Tuncel, MS Akkaya Biochemical and biophysical research communications 413 (1), 111-115, 2011 | 14 | 2011 |
| A high-resolution map of the human small non-coding transcriptome T Fehlmann, C Backes, J Alles, U Fischer, M Hart, F Kern, H Langseth, ... Bioinformatics 34 (10), 1621-1628, 2018 | 11 | 2018 |
| TaME-seq: An efficient sequencing approach for characterisation of HPV genomic variability and chromosomal integration S Lagström, SU Umu, M Lepistö, P Ellonen, R Meisal, IK Christiansen, ... Scientific reports 9 (1), 1-12, 2019 | 10 | 2019 |
| Circulating small non-coding RNAs associated with age, sex, smoking, body mass and physical activity TB Rounge, SU Umu, A Keller, E Meese, G Ursin, S Tretli, R Lyle, ... Scientific reports 8 (1), 1-13, 2018 | 5 | 2018 |
| A 10 year prediagnostic followup study shows that serum RNA signals are highly dynamic in lung carcinogenesis SU Umu, H Langseth, A Keller, E Meese, Ĺ Helland, R Lyle, TB Rounge Molecular Oncology, 2019 | 3 | 2019 |
| A meta-analysis of bioinformatics software benchmarks reveals that publication-bias unduly influences software accuracy PP Gardner, JM Paterson, F Ashari-Ghomi, SU Umu, S McGimpsey, ... BioRxiv, 092205, 2017 | 3 | 2017 |
| Trainer: A general-purpose trainable short biosequence classifier H Oqul, AT Kalkan, SU Umu, MS Akkaya Protein Pept Lett, 2013 | 2 | 2013 |
| PO-096 Natural variation in serum small non-coding rnas–potential biomarkers of cancer SU Umu, R Lyle, H Langseth, TB Rounge ESMO Open 3 (Suppl 2), A263-A264, 2018 | 1 | 2018 |
| RNA Sequencing of Hepatobiliary Cancer Cell Lines: Data and Applications to Mutational and Transcriptomic Profiling D Scherer, MD Dávila López, B Goeppert, S Abrahamsson, ... Cancers 12 (9), 2510, 2020 | | 2020 |
| Serum RNA profiling in the 10-year period prior to diagnosis of testicular germ cell tumour J Burton, SU Umu, H Langseth, T Grotmol, TK Grimsrud, TB Haugen, ... medRxiv, 2020 | | 2020 |
| PO-073 Small non-coding RNA in serum from testicular germ cell tumour patientsidentified by machine learning J Burton, H Hammer, S Umu, H Langseth, T Grotmol, T Grimsrud, ... ESMO Open 3 (Suppl 2), A255-A256, 2018 | | 2018 |
| Impact of age, sex, smoking, body mass and physical activity on circulating small non-coding RNA expression profiles TB Rounge, SU Umu, A Keller, E Meese, G Ursin, S Tretli, R Lyle, ... Cancer Research 78 (13 Supplement), 524-524, 2018 | | 2018 |
| Natural avoidance of stochastic mRNA: ncRNA interactions can be harnessed to control protein expression levels SU Umu, AM Poole, RCJ Dobson, PP Gardner bioRxiv, 033613, 2016 | | 2016 |
| Investigating prokaryotic transcriptomes and the impact of crosstalk between noncoding RNA and messenger RNA interactions SU Umu University of Canterbury, 2016 | | 2016 |
| TRAINER: A General-Purpose Trainable Short Biosequence Classifer H OĞUL, A Kalkan, S Umu, M AKKAYA | | 2013 |
| Mining fungal effector candidates in biotrophic plant pathogens: rusts and mildews SU Umu | | 2012 |
Trine B RoungeCancer Registry of NorwayVerified email at kreftregisteret.no
